Abstract
•The governing parameters for creep damage mechanism were highlighted. Creep crack growth is characterized as continuum damage mechanics (CDM) for prediction of accumulated damage, residual life, and rupture given the applied stress and temperature.•Five most established creep models of Omega, Norton Bailey, Theta Projection, Sine Hyperbolic and Kachanov Rabotnov were considered for the study, as their merits and drawbacks in predicting equipment service life were discussed.•Critical analysis was presented to estimate the accuracy at high temperature and pressure conditions, as well as on the creep responses on crack initiation, growth and rupture of the material.•Propose development of improved material model for creep prediction in similar practice, through creep power laws. The enhanced model should be able to reduce the margin of error between predicted and actual rupture time of the material, under constant stresses and at elevated temperatures.
Traditionally, the detection of the creep responses has been carried out using empirical methods containing multiple adjustable parameters. This makes it very difficult to estimate the material’ creep behaviour outside the original data set. In recent years, the researchers have devised simple models for the prediction of creep properties, covering dislocation, particle and solid solution hardening. There are no adjustable parameters in these versions, these models are further explored in this study in order to establish an optimized solution for the creep analysis. This paper presents a review of the five established models which are Norton Bailey, Omega, Kachanov-Rabotnov, Theta projection and Sine hyperbolic models. In depth analysis of these five creep models was conducted, highlighting the significance of their application and the demerits of their usage. First, creep phenomenon was explained, followed by creep mechanism and creep crack growth characterization. Historical development of the models was explained briefly followed by creep material models limitations. With the help of case studies, pros and cons of using the models were further highlighted and comparison was drawn among the models. Finally, future development of creep prediction models and their scope came into limelight. It is anticipated that this review paper will become a reliable reference for the selection of creep prediction models.